1. Field of the Invention
This invention relates generally to the fields of knowledge management systems, information portals, research, catalog search, search engines, and data miners, and particularly, to a comprehensive customer self service system for resource search and selection implementing novel graphical user interface and machine learning components.
2. Discussion of the Prior Art
Currently there exist many systems designed to perform search and retrieval functions. These systems may be classified variously as knowledge management systems, information portals, search engines, data miners, etc. However, providing effective customer self service systems for resource search and selection presents several significant challenges. The first challenge for current systems with query capability is that serving queries intelligently requires a large amount of user supplied contextual information, while at the same time the user has limited time, patience, ability and interest to provide it. The second challenge is that searching without sufficient context results in a very inefficient search (both user time and system resource intensive) with frequently disappointing results (overwhelming amount of information, high percentage of irrelevant information). The third challenge is that much of a user""s actual use and satisfaction with search results differ from that defined at the start of the search: either because the users behave contrary to their own specifications, or because there are other contextual issues at play that have not been defined into the search.
While many search systems today use an iconic interface to capture the query, they do not incorporate a rich set of contextual attributes and, they do not incorporate the user""s past interaction. The prior art has separately addressed the use of the history of interaction with the user or their current service environment to provide context for a resource search and selection system. The prior art also assumes the shallow context of a single user query stream focused on a single topic. A major limitation of these approaches is to continue to burden the user with providing substantial contextual information and inability of such systems to apply specific user context to improve resource selection for other users on the same subject. While some search systems today use an iconic interface to display the results of a search, they do not include ranking by sets of contextual decision criteria. Users are forced to select from returned resources on the basis of content alone and actually begin using the resources before they realize the resources are not appropriate in the user""s complete context. While some search systems today may track a user""s use of the system, they don""t use that information to develop a better query interface over time and to better inform the search both real time and historically regarding this user, particularly in a predictive or directive fashion.
One consequence of these process and systems limitations is that the primary user will frequently turn to an intermediate person to provide them with the desired end-product, or to research and analyze the various resources that may be available to them. Generally speaking this human resource is not consistently accessible and/or available in the time, timeframe, and quantity desired. Generally speaking, this human resource comes at an additional cost (direct or indirect) in the process, creating an expensive solution to the user""s need than a self service approach could provide.
It would be highly desirable to provide a customer self service system that entirely eliminates the need to utilize intermediate persons in some instances, or, at a minimum, is capable of assisting these intermediate persons to be more effective.
While the end user (or their selected intermediaries) may xe2x80x9csearchxe2x80x9d a broad universe of resources, seeking the specific instances that will serve, there is another set of potential users who need to survey the same data, but for the converse rationale. Individuals and organizations who are developing and supplying the resources being queried, look at their xe2x80x9cproductxe2x80x9d and want to know what resources may exist to compete with, complement, precede, follow, or obviate the need for their product, it""s marketing or delivery channel. The limitations in the existing systems impact these individuals and organizations by reducing effectiveness and increasing cost of market research, market planning, strategic planning and implementation activities.
Some representative prior art database/resource search, retrieval and selection systems that requires some measure of interactivity and implements graphical or visual interfaces include those described in U.S. Pat. No. 5,303,361 entitled xe2x80x9cSearch and Retrieval Systemxe2x80x9d; U.S. Pat. No. 5,524,187 entitled xe2x80x9cWorlds-Within-Worlds Nested Display and Interaction System and Methodxe2x80x9d; U.S. Pat. No. 5,546,516 entitled xe2x80x9cSystem and Method for Visually Querying a Data Set Exhibited in a Parallel Coordinate Systemxe2x80x9d; U.S. Pat. No. 5,600,835 entitled xe2x80x9cAdaptive Non-Literal Text String Retrievalxe2x80x9d; U.S. Pat. No. 5,608,899 entitled xe2x80x9cMethod and Apparatus for Searching a Database by Interactively Modifying a Database Queryxe2x80x9d; U.S. Pat. No. 5,710,899 entitled xe2x80x9cInteractive Selectors for Selecting Subsets of a Set of Valuesxe2x80x9d; U.S. Pat. No. 5,768,578 entitled xe2x80x9cUser Interface for Information Retrieval Systemxe2x80x9d; U.S. Pat. No. 5,841,437 entitled xe2x80x9cMethod and Apparatus for Interactive Database Queries via Movable Viewing Operation Regionsxe2x80x9d; U.S. Pat. No. 5,918,217 entitled xe2x80x9cUser Interface for a Financial Advisory Systemxe2x80x9d; U.S. Pat. No. 5,930,501 entitled xe2x80x9cPictorial User Interface for Establishing Time of Day and Geographical or Environmental Context on a Computer Display or Other Monitorxe2x80x9d; U.S. Pat. No. 5,974,412 entitled xe2x80x9cIntelligent Query System for Automatically Indexing Information in a Database and Automatically Categorizing Usersxe2x80x9d; U.S. Pat. No. 5,999,927 entitled xe2x80x9cMethod and Apparatus for Information Access Employing Overlapping Clustersxe2x80x9d; U.S. Pat. No. 5,787,422 entitled xe2x80x9cMethod and Apparatus for Information Access Employing Overlapping Clusters; U.S. Pat. No. 6,105,023 entitled xe2x80x9cSystem and Method for Filtering a Document Streamxe2x80x9d; and, an article by Susan Feldman entitled xe2x80x9cThe Answering Machine,xe2x80x9d in Searcher: The Magazine for Database Professionals, 1, 8, January, 2000/58.
Representative prior art references addressing the issue of providing some element of context to search and retrieval systems includes U.S. Pat. No. 5,619,709 entitled xe2x80x9cSystem and Method of Context Vector Generation and Retrievalxe2x80x9d; U.S. Pat. No. 5,794,178 entitled xe2x80x9cVisualization of Information Using Graphical Representations of Context Vector Based Relationships and Attributesxe2x80x9d; U.S. Pat. No. 6,014,661 entitled xe2x80x9cSystem and Method for Automatic Analysis of Data Bases and for User-Controlled Dynamic Queryingxe2x80x9d; U.S. Pat. No. 6,097,386 entitled xe2x80x9cData Processing System Having Context Sensitive Visual Feedback for User Interface Controls and Method Thereforxe2x80x9d.
The prior art has additionally addressed the use of some of the features of the resources (content and other) in relation to the user""s context and/or prior use of other resource search and selection systems, for selection of responses to current user""s queries. Representative prior art approaches systems described in U.S. Pat. No. 5,724,567 entitled xe2x80x9cSystem for Directing Relevance-Ranked Data Objects to Computer Usersxe2x80x9d; U.S. Pat. No. 5,754,939 entitled xe2x80x9cSystem for Generation of User Profiles For a System For Customized Electronic Identification of Desirable Objectsxe2x80x9d; and, U.S. Pat. No. 5,321,833 entitled xe2x80x9cAdaptive Ranking System for Information Retrievalxe2x80x9d.
While the prior art has addressed the issues of database searching, dynamic query formulation, and the visual representation of multidimensional data, newer search engines are just beginning to use some of these ideas to express queries and results. There has heretofore never been an information search and retrieval method which facilitates the efficient location of relevant resources by the busy user by enabling the expression of a user""s context as part of the query, and the relevance of the results to that context. Further, there is notably absent in the art one system that provides an end-to-end solution integrating the user and system, the content and user context, and the search and result, that would enable a self service resource search and selection system to learn from each and all users and make that learning operationally benefit all users over time.
It is an object of the present invention to provide a novel customer self service resource search and selection system that captures the user""s question or search parameters, researches all the relevant resources to directly answer the question or to better inform the user about the subject area, presents the resources in a fashion that clarifies understanding of the resource opportunity and, facilitates decision making/selection between the various resources.
It is another object of the present invention to provide a novel customer self service resource search and selection system that performs an initial process resulting in the discovery and/or acquisition of the search responses, and a secondary process resulting in system-enabled xe2x80x9clearningxe2x80x9d about both users and resources which enables improved performance by the system both within one session and subsequently over time.
It is a further object of the present invention to provide an intuitive graphical user interface (GUI) for a customer self service system enabling resource search and selection, the GUI providing elements enabling entry of query search terms, selection and fine tuning of user context definitions associated with a query (context includes, for example, the user""s computing environment), establishment of inclusionary and exclusionary resource filters, and specification of resource priorities including the selection, sequencing and weighting of relevant resource evaluation criteria.
It is yet another object of the present invention to provide an intuitive GUI for a customer self service system for resource search and selection that permits visualization and exploration and manipulation of the response set through multidimensional context variables and, particularly presents the resource response set in a way which clearly illustrates their degree of fit with the user""s most important context variables, as indicated by their prior usage of the system, as well as by context choices for a current user query.
It is still another object of the present invention to provide in a customer self service system for resource search and selection, a mechanism for supplying annotations to query response sets that affect the order that these resources are presented to the user by a visualization system. Further to this object, it is an additional object of the invention to implement in the annotation mechanism, a supervised learning algorithm wherein training data utilized for this algorithm is derived from prior user interactions and the annotation function is optimized based on an annotation scoring metric.
It is another object of the present invention to provide in a customer self service system for resource search and selection, a mechanism for providing a response set based on user queries and derived user contexts that is adaptable for modifying output response sets in accordance with different user contexts and user interactions as they change over time. Further to this object, it is another object of the present invention to provide an adaptive indexing function that implements a supervised learning algorithm to produce a resource response set based on a user query.
It is yet a further object of the present invention to provide in a customer self service system for resource search and selection, a mechanism for applying user context for the purpose of more efficient resource dispersion and, for improving the relevance of search results for a given user in their current context without requiring the user to explicitly train the system. Further to this object, it is an object of the present invention to implement a supervised machine learning algorithm that receives a set of historical user interaction records in order to classify context attributes that are relevant for that particular user of the system.
It is yet still another object of the present invention to provide in a customer self service system for resource search and selection, an automatic clustering process that discovers related queries and enables the inference of new relevant context terms and generation of corresponding graphical icons used to describe the users and their interactive situations. Further to this object, it is an object of the present invention to provide an unsupervised machine learning technique for enabling clustering of sets of user interaction records to discover groups of similarly situated queries.
According to the invention, there is provided a customer self service system and method for performing resource search and selection. The method includes steps of providing an interface enabling entry of a query for a resource and specification of one or more user context elements, each element representing a context associated with the current user state and having context attributes and attribute values associated therewith; enabling user specification of relevant resource selection criteria for enabling expression of relevance of resource results in terms of user context; searching a resource database and generating a resource response set having resources that best match a user""s query, user context attributes and user defined relevant resource selection criteria; presenting said resource response set to the user in a manner whereby a relevance of each of the resources being expressed in terms of user context in a manner optimized to facilitate resource selection; and, enabling continued user selection and modification of context attribute values to enable increased specificity and accuracy of a user""s query to thereby result in improved selection logic and attainment of resource response sets best fitted to the query. More particularly, adaptive algorithms and supervised and unsupervised learning sub-processes are implemented to enable the self service resource search and selection system to learn from each and all users and make that learning operationally benefit all users over time.
Advantageously, such a customer self service system is applicable to a variety of customer self service domains including, but not limited to: education, real estate and travel.